Abstract
Diagnosing the minimal set of faults capable of explaining a set of given observations, e.g., From sensor readouts, is a hard combinatorial optimization problem usually tackled with artificial intelligence techniques. We present the mapping of this combinatorial problem to quadratic unconstrained binary optimization (QUBO), and some preliminary experimental results of instances embedded onto the 509 qubit NASA-Google-USRA quantum annealer. This is the first application with the route Problem > QUBO > Direct embedding into quantum hardware, where we are able to implement and tackle problem instances with sizes that go beyond previously reported toy-model proof-of-principle implementations. We believe that these results represent a significant leap in the solution of problems via direct-embedding quantum optimization.
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